Trait summary

Determining the optimal K from the bNMF run summary

The plot “Convergence Scores by K” helps analyze which K value performs better in terms of convergence.


Determining the optimal cutoff for clustering weights (parameters: N, M)

1) Fit a 1st line to the top N% of weights

2) Fit a 2nd line to the M% of tail weight

3) Using the remaining weights from top N% to last M%, check if they have shorter distance to 1st or 2nd line

4) The first weight that has a shorter distance to 2nd line (defined by long tail) is selected as the cutoff.

Optimal weight cutoff: 0.59778 (includes top 8.1% of variants)


Cluster Weights

Weights above cutoff are highlighted




Manhattan plot

Cluster Weight Heatmaps

Column label color correspond to the cluster with the column’s highest weight


Genes x Clusters

Variants x Clusters

Cluster Circle Plots

Only includes variants and phenotypes with weights above cutoff

Blue = negative trait
Red = positive trait
Green = variant